Reinsurers insure risks of primary insurers or other reinsurers (i.e. risks of cedents). Reinsurance includes proportional and non-proportional reinsurance. In the case of proportional insurance, the reinsurer participates for a defined share or proportion in the liabilities, premiums, and claims of a cedent's reinsured portfolio. In the case of non-proportional reinsurance, the reinsurer's liability is only triggered when the reinsured policy or portfolio of the cedent is affected by a loss, which exceeds a specific amount, the so-called deductible. Typically, the amount of loss exceeding the deductible is assumed by the reinsurer up to a defined treaty limit (upper limit of cover). There is exceeding loss (XL) reinsurance for individual losses, affecting a single (re)insured risk (e.g. a person or item of property) which is triggered by one and the same event (per risk), and for losses with accumulation, i.e. multiple policies or risks which are exposed to the same area of loss or risk and can be affected by the same ordinary loss occurrence (per event). For calculating his premium, the reinsurer has to determine quantitatively the risk of having to cover a loss of a cedent. An expected loss is calculated based on the number of persons involved in a loss event (e.g. an accident), the deductible of the cedent, the treaty limit, the number of persons or groups of persons insured by the cedent, and statistical data regarding the persons or groups of persons insured by the cedent. Thus, the expected loss is calculated based on the probabilities that a certain number of persons is involved in a loss event, that a certain loss amount is reached by a loss event involving a certain number of persons, and that a certain number of persons insured by the cedent are involved in a loss event. Specifically, the expected loss is calculated by the multiplication of these probability distributions. The most common approach used for calculating the expected loss is the so-called Strickler method, described for example, by G. Feilmeier and G. Segerer, “Einige Anmerkungen zur Rückversicherung von Kumulrisiken nach dem Verfahren Strickler”, Blätter der Deutschen Gesellschaft für Versicherungsmathematik 14, 1980. From statistical data, the Strickler method determines a probability distribution indicating the probability that at least a certain number N of persons are affected in a loss event. The resulting probability distribution is converted into a probability distribution indicating the probability that an exact number of N persons are affected by a loss event. Furthermore, based on a probability distribution for the accumulated loss amount per affected person, a probability distribution for the loss amount of N affected persons is calculated from the loss amount per affected person through N−1-fold convolution. A probability distribution is calculated for the loss caused by an event with at least N affected persons through multiplication of the distribution of the probability that exactly n persons are affected by a loss event and the distribution of the loss amount for n persons affected, for the range of n≧N. To consider the circumstances of the cedent, the result is multiplied by the percentage of the insured that are insured by the cedent. Therefrom, based on the treaty limit and the deductible of the cedent, an expected value is calculated for the loss to be covered by the reinsurer and used as a basis for calculating the risk premium. For the distribution of the loss amount, the Strickler method assumes an exponential distribution.
Although the Strickler method does provide a way for estimating the risk of the reinsurer, the expected values calculated according to the Strickler method are quite unreliable. Typically, the statistical standard deviation is a multiple of the expected value. To improve the reliability of the Strickler method, specific distributions of the loss amount of the persons affected by a loss event are included in the calculation. Another weakness of the Strickler method is based on the fact that all cedents are assumed to be affected equally by a loss event. This weakness is improved by dividing the population concerned (e.g. population of a state or a region) into different classes, wherein the insured persons of the population considered are distributed equally in a class. A total probability of at least N persons being affected by a loss event is calculated from the probability that in a class a certain number of persons, insured by a certain cedent, are affected by a loss event. A computer-based system, configured to execute automatically the Strickler method, requires hardware and software resources for storing, maintaining, and accessing statistical data. Due to the fact that the frequency of large loss events may vary strongly over time, long time periods are used to collect the statistical data. Consequently, further hardware and software resources must be provided for capturing and storing the statistical data over long time periods, for example over fourteen or more years. The heavy dependency on long-term statistical data makes computer-based systems for executing the Strickler method inflexible. Moreover, this dependency increases the risk that the basis for the calculation, particularly the distribution of the loss frequency and/or loss amount, changes compared to the statistical data used and stored in the system. Consequently, additional hardware and software resources must be provided for updating constantly and continuously the statistical data. For that purpose the system must be interconnected via telecommunications networks with various data sources in different geographical regions. Furthermore, the system must be provided with software resources for merging and consolidating the statistical data provided by the different sources in possibly different formats.